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Note: This Paper Has Not Yet Undergone Formal Peer Review Note: This paper has not yet undergone formal peer review Evaluating the infodemic: assessing the prevalence and nature of COVID- 19 unreliable and untrustworthy information in Aotearoa New Zealand’s social media, January-August 2020 6 September 2020 Max Soar1,2, Victoria Louise Smith1,3, M.R.X. Dentith4, Daniel Barnett5,6, Kate Hannah1,2,7, Giulio Valentino Dalla Riva8, Andrew Sporle5,6 1. Te Pūnaha Matatini: Centre of Research Excellence for Complex Systems and Networks, New Zealand 2. Centre for Science in Society, Te Herenga Waka – Victoria University of Wellington 3. Faculty of Science, University of Auckland 4. University of Waikato 5. Department of Statistics, University of Auckland 6. iNZight Analytics 7. Department of Physics, University of Auckland 8. School of Mathematics and Statistics, University of Canterbury Abstract The arrival of the COVID-19 pandemic in Aotearoa New Zealand saw New Zealanders presented with the accompanying infodemic. Aotearoa New Zealand’s experience, which is characterised by mis- and dis-information, as well as the emergence of a number of conspiracy theories, is linked to international patterns within the COVID-19 infodemic overall, but also displays significant situated and differential themes and impacts. We evaluate the prevalence of the COVID-19 infodemic in social and mainstream media February-August 2020, and analyse the narrative intent and social or political discourses of the content collated. In evaluating the nature of COVID-19 narratives over this time period, we find that there are significant changes in the types of discourses these narratives engage with, with an increasing prevalence of conspiracy narratives noted since the re-emergence of community transmission in August. Assessing the impact of these unreliable and/or untrustworthy narratives and their sources, including narrators, we develop preliminary understanding of the ways in which these narratives are at work in Aotearoa New Zealand. Introduction The COVID-19 outbreak originated in Wuhan, China, in November 2019 (World Health Organisation, 2020b) before spreading globally to become a pandemic in March 2020 (World Health Organisation, 2020c). Between February and May 2020, Aotearoa New Zealand recorded 1,504 cases of COVID-19 before eliminating community transmission of the virus in June 2020. Re- emergence of community transmission was announced on 11 August 2020; as of 3 September 2020 150 cases have been identified within a new, ‘South Auckland’ cluster; together with cases at the border, Aotearoa New Zealand’s total number of confirmed and probable cases is 1759. Local, regional, and global infodemics map to the spread of the pandemic (Islam et al., 2020). An infodemic is “an over -abundance of information—some accurate and some not—that makes it hard for people to find trustworthy sources and reliable guidance when they need it” (World Health Organisation, 2020a). Recent international surveys of the COVID-19 infodemic have tended to be international in scope, with a focus on the public health impacts of inaccurate and unreliable information. This preliminary investigation, which tracks social and mainstream media content since the beginning of the pandemic’s impact in Aotearoa New Zealand, seeks to understand the prevalence of misinformation, disinformation, and mal-information within the infodemic. We then explore the nature of that content investigating if and how these infodemic discourses fit with known conspiracy theories. We describe the changes in both nature and prevalence of these narratives from Aotearoa New Zealand’s first community outbreak and its re-emergence, showing how the infodemic has shifted in discursive nature over time. What is measured here is level of amplification: how much are these ideas being talked about? Who is talking about them? Level of active belief has not yet been measured. Aotearoa New Zealand’s communities have differential experiences of past pandemics, different measures of health and wellbeing, and different experiences of state services and state intervention. The pandemic and infodemic are also taking place within different nation-states, with different political systems, worldviews, and approaches to healthcare and the role of government. These contexts necessarily inform community and individual responses to the overabundance of information experienced. Understanding how the infodemic has presented in Aotearoa New Zealand enables us to better evaluate ways in which unreliable and untrustworthy information differentially impacts our communities. Methods Study settings and data collection We assembled a team of computational and data scientists, public understanding of science and technology scholars, and conspiracy theory scholars with diverse disciplinary backgrounds in August 2020 to collate and analyse Aotearoa New Zealand’s publicly available social media, mainstream media, and public discourse from mid-January 2020 to the present. A core team has been monitoring these media sources since the beginning of the infodemic in Aotearoa New Zealand. This collation of 122009 tweets is mostly limited at present to English-language sources; future studies will endeavour to collate more widely in other key languages in use in Aotearoa New Zealand, including Te Reo Māori, a number of Pacific languages, and Mandarin. Study definitions We use the following definitions from Berentson-Shaw and Elliot (2020): Misinformation “false information that people didn’t create with the intention to hurt others” 2 Disinformation “false information created with the intention of harming a person, group, or organization, or even a country” Mal-information “true information used with ill intent” We note that mal-information is present in some discourses active within Aotearoa New Zealand’s social and mainstream media. These types of unreliable or untrustworthy information often appear in the form of conspiracy theories. Acknowledging that there is considerable debate as to what counts as a ‘conspiracy theory’ (see Dentith, 2018), we work with the following, general definition, which defines them as purported explanations which cite a conspiracy as the salient cause of some event or phenomenon. Critically, particularly in the context of COVID-19, belief in some conspiracy theories is not unreasonable, because there exist real conditions or lived experiences which make them resonate. Māori scholar and advocate Tina Ngata has described how “these theories aren’t a big stretch for a group who’ve had 180 years of the state riding roughshod over their rights” (Ngata, 2020). In these circumstances, communities and individuals must work to ascertain when the evidence suggests we ought to infer the existence of a conspiracy, and when we should prefer non-conspiratorial explanations (Dentith, 2016). In categorizing the infodemic, we have used theme, narrative, and meta-narrative as critical definitional terms. Here, we use ‘theme’ to describe the topic or main meaning of a piece of information, while ‘narrative’ is used to describe the story within which that meaning is located, and includes its structure, function, substance, and mode/s of performance (Allen, 2017). Meta-narrative here is used simplistically to refer to over-arching narratives or tropes, some of which may rightly be regarded as conspiracy theories and others which reflect cultural norms and mores. Data collection We collected publicly available tweets using the R package rtweet and the Python module Twint. We integrated the dataset with the aggregate information made available daily by FBK CoMuNe lab (Gallotti et al., 2020). The FBK analysis combines computational analysis of Twitter content for sentiment, reliability of sources, and prevalence of accounts classified as bots in the twittersphere. We searched and aggregated tweets using two different methods: we queried for a list of terms (“covid”, “coronavirus”, “virus”, “lockdown”) and their variations, either as hashtags or as words contained in the tweets, and we queried for mention of specific user accounts that have a critical role in the pandemic response (including an extensive list of NZ MPs, health authorities, and science communicators). We collected data geotagged as originating from Aotearoa New Zealand. Where publicly available, narratives were reviewed via other social media platforms including Facebook, Instagram, YouTube and independent websites/blogs. Using FBK CoMuNe lab’s categorisations as a starting point, we merged publicly available lists of news sources, both social and mainstream, identified as unreliable, and we localized that list considering social and mainstream news outlets relevant to Aotearoa New Zealand. We monitored the prevalence of the word “conspiracy” (and “misinformation”, “disinformation”, “debunking”) querying the Global Data on Events, Location 3 and Tone database (GDELT). GDELT is an open-source global database of society, supported by Google’s Jigsaw tool (Leetaru & Schrodt, 2013). Analysis We established the reliability of the news sources contained in each tweet we collected by matching it with the collated list of reliable and unreliable sources, excluding links to non-relevant websites. For each day in our observational window, we assessed the percentage of unreliable and reliable sources. The matching was performed using R. The collated text material, which includes found text consisting of social media posts and mainstream media articles in addition to the computationally retrieved Twitter data described above, has been analyzed
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